developing production-grade machine learning models, scaling LLM systems, and mentoring teams. Key requirements typically include 5+ years of experience, advanced Python proficiency, and expertise in cloud platforms. [1, 2]Role Overview
- Job Title: Senior AI / ML Engineer
- Experience Level: 5–7+ Years
- Core Focus: Designing, scaling, and operationalizing production-grade AI, Machine Learning, and Generative AI applications. [1, 2]
Key Responsibilities
- AI & GenAI Development: Design and implement LLM-powered applications using Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and semantic search. [1]
- MLOps & Production: Build scalable data and model-serving pipelines, enforce CI/CD for ML, and monitor system performance, latency, and data drift. [1, 2, 3]
- System Integration: Integrate AI capabilities into enterprise platforms via secure REST APIs and microservices. [1, 2]
- Leadership & Strategy: Partner with cross-functional product and engineering stakeholders while mentoring junior developers. [1]
Required Qualifications
- Education: Bachelor's or Master’s degree in Computer Science, AI, ML, or a related quantitative field.
- Technical Stack: Advanced Python and SQL, with hands-on experience using frameworks like PyTorch, TensorFlow, LangChain, or LlamaIndex.
- Cloud & Infrastructure: Experience deploying scalable workloads on cloud providers like Microsoft Azure AI Services, AWS, or Google Cloud Platform
Pay: ₹480,431.82 - ₹1,789,378.97 per year
Work Location: In person
